Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "tsfile/tsfile_py_cpp.pyx", line 567, in tsfile.tsfile_py_cpp.tsfile_reader_new_c
              tsfile.exceptions.FileOpenError: 28: 
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 271, in _split_generators
                  scan = self._scan_metadata(all_files)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 318, in _scan_metadata
                  with self._open_reader(file) as reader:
                       ~~~~~~~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/tsfile/tsfile.py", line 742, in _open_reader
                  return TsFileReader(file)
                File "tsfile/tsfile_reader.pyx", line 323, in tsfile.tsfile_reader.TsFileReaderPy.__init__
              SystemError: <class '_weakrefset.WeakSet'> returned a result with an exception set
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Pickup Carrot No Subversion TsFile

This dataset is an Apache TsFile conversion of argus-systems/pickup-carrot-no-subversion, a LeRobot v2.1 robot-manipulation dataset created with LeRobot.

Modalities: Time-series. The converted repository contains numeric robot observations, actions, frame timing, episode/task tags, and mirrored source metadata. Camera videos remain in the original Hugging Face dataset.

Source Dataset

  • Original dataset: argus-systems/pickup-carrot-no-subversion
  • Repository owner: argus-systems
  • License: Apache-2.0
  • Robot type: trossen_ai_stationary; Trossen subversion: v1.0
  • Task: Pick up the carrot and put it in the bowl.
  • Sampling rate: 30 fps
  • Source frame files: 58 Parquet episodes, 25,922 rows (episode indexes 1–38, 40–49, and 51–60)
  • Source frame layout: data/chunk-000/episode_{episode_index:06d}.parquet
  • Source video layout: videos/chunk-000/{video_key}/episode_{episode_index:06d}.mp4
  • Video streams: observation.images.cam_high, cam_low, cam_left_wrist, and cam_right_wrist (58 MP4 files per stream; 232 total)
  • The source card has no separate formal author, paper, or completed citation. Its meta/info.json advertises 61 episodes/27,261 frames, while the current revision contains the 58 files and 25,922 rows above.

Converted Files

  • TsFile: data/argus_systems_pickup_carrot_no_subversion.tsfile
  • Table: argus_systems_pickup_carrot_no_subversion
  • Rows: 25,922
  • Episodes represented: 58
  • Time precision: milliseconds
  • meta/ is mirrored from the source; meta/info.json is updated with the TsFile path and conversion record.

Schema

Time is round(timestamp * 1000) milliseconds. The source timestamp column is dropped because it is redundant with Time / 1000 seconds and restarts within each episode.

TAG columns (TsFile table/device dimensions):

  • episode_index
  • task_index

Scalar FIELD columns:

  • frame_index (INT64)
  • sample_index (INT64), renamed from source index

Flattened FLOAT FIELD groups:

  • action[14] → action_0 … action_13
  • observation.state[14] → observation_state_0 … observation_state_13

Conversion Notes

  • The shared config-driven lerobot converter was used through the local dataset-specific entry point. All 58 source Parquet files are merged into one table-model TsFile; filter by the TAG columns to select an episode or task.
  • Vector columns are flattened to scalar fields, preserving the full source prefix and replacing . with _. No numeric rows or vector dimensions are intentionally dropped.
  • Encoding policy: FLOAT/DOUBLE = GORILLA + LZ4; INT32/INT64 and Time = TS_2DIFF + LZ4; BOOLEAN would use RLE + LZ4; TAG values use the TsFile table/device TAG mechanism. The source schema contains no BOOLEAN fields.
  • Videos are not duplicated here. They remain in the original repository under videos/. Numeric rows remain frame-aligned through episode_index and frame_index.

Validation

VALIDATION.md and validation_report.json are local artifacts documenting TsFile readability, schema, encoding policy, and row-count equality (25,922 rows). They are intentionally not part of an upload payload.

Usage

from tsfile import TsFileReader

reader = TsFileReader("data/argus_systems_pickup_carrot_no_subversion.tsfile")
table_name = "argus_systems_pickup_carrot_no_subversion"
columns = ["episode_index", "task_index", "frame_index", "sample_index", "action_0", "observation_state_0"]
with reader.query_table(table_name, columns, batch_size=65536) as result:
    batch = result.read_arrow_batch()
    print(batch.to_pandas().head())
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